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07/24/2023
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
Despite the success of diffusion models (DMs), we still lack a thorough ...
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03/10/2023
Tradeoff of generalization error in unsupervised learning
Finding the optimal model complexity that minimizes the generalization e...
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02/24/2023
Unsupervised Discovery of Semantic Latent Directions in Diffusion Models
Despite the success of diffusion models (DMs), we still lack a thorough ...
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11/29/2022
Mirror descent of Hopfield model
Mirror descent is a gradient descent method that uses a dual space of pa...
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09/07/2021
Scale-invariant representation of machine learning
The success of machine learning stems from its structured data represent...
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02/15/2021
Compression phase is not necessary for generalization in representation learning
The outstanding performance of deep learning in various fields has been ...
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01/28/2021
Inference of stochastic time series with missing data
Inferring dynamics from time series is an important objective in data an...
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11/27/2020
Tractable loss function and color image generation of multinary restricted Boltzmann machine
The restricted Boltzmann machine (RBM) is a representative generative mo...
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05/18/2020
Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles
Machine learning shows remarkable success for recognizing patterns in da...
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09/10/2019
Inverse Ising inference from high-temperature re-weighting of observations
Maximum Likelihood Estimation (MLE) is the bread and butter of system in...
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12/12/2015